Augmented and virtual reality, indoor navigation, and building simulation software is rapidly changing. The ability to automatically and rapidly generate a 3D mesh of building surfaces from static or mobile scanning systems is important to many fields, such as augmented and virtual reality, gaming, simulation, architecture, engineering, construction, and emergency response services. Existing 3D meshing algorithms applied to the 3D point cloud of building interiors typically mesh the objects inside the buildings and the building structure elements such as floors, walls, and ceilings together in one mesh. Unfortunately, such a single mesh does not faithfully represent the building structure elements due to clutter introduced by objects such as furniture or fixtures and, as such, may result in inaccurate 3D architectural model of the building, or 2.5D or 2D floor plans of the building. In addition, conventional single mesh algorithms introduce storage and transmission inefficiencies because all elements are represented with the same level of detail resulting in a large number of triangles, even though floors and walls can, in fact, be represented with much fewer triangles since they are usually planar.
As such, methods for indoor 3D surface reconstruction and 2D floor plan recovery utilizing segmentation of building and object elements are presented herein.